1. Field of the Invention
This invention involves an improved method and apparatus of signal processing for radar systems. In particular, the present invention pertains to dual path radar signal processing in which high SNR radar return signals are coherently integrated for signal detection and low SNR signals are coherently integrated by fast Fourier transforms and additionally noncoherently integrated for signal detection.
2. State of the Art
Radar systems transmit signals and detect echos reflected from distant target objects to detect the target objects. Detection of a target object includes, for instance, determining the position, direction of movement, velocity and acceleration of target objects. Radar systems typically transmit signals of predetermined frequencies in the form of pulses or waveforms transmitted at varying frequencies. Transmitted radar waveforms of varying frequency can be used to implement linear frequency modulated chirp pulses or some such signal encoding schemes. The transmitted signals can vary in frequency, for example, from the megahertz range up to light wave frequencies in the visible spectrum. Conventional radar systems can have a co-located transmitter and receiver, or can have a transmitter and receiver located at different positions.
Signal strength is important in discerning information about a target object. Because the signal strength of the return signal varies inversely to the fourth power with the distance R between the radar system and the target (1/R.sup.4), the signal strength of a return signal tends to be weak in comparison to the transmitted signal. In a addition to the distance between the radar system and the target, signal strength and quality are also affected by radar parameters and target variables. Radar aperture, transmit power and amplifier efficiencies are examples of radar parameters which affect a radar system's target detection ability. Likewise, target size, shape, target object material, and target velocity/acceleration, also affect the return signal strength and signal quality. For instance, as target objects, missiles can be especially challenging to detect because they tend to be fast moving, small, targets With a high degree of acceleration uncertainty. In addition, as radar return signals diminish to the level of background noise they tend to be very difficult to detect.
Signal processing can be used to detect weak radar return signals, and to discern the Doppler characteristics of return signals for determining position, velocity and acceleration of the target object. As the signal-to-noise ratio (SNR) decreases, signal processing becomes more important for signal detection. Signal processing also becomes more computationally burdensome as the return signal SNR becomes smaller, since the return signal blends into the background noise. In general, low SNR signals with fewer unknown variables are easier to detect than low SNR signals with more unknown variables. For example, signals having a known acceleration value are easier to detect than signals with an unknown acceleration component.
In order to reduce the unknown variables of return signals and thus enhance signal processing, radar systems typically transmit coherent radar signals. Signal coherence means that the phase is continuous from one transmitted signal to the next, is if the signals were chopped out of the same continuous waveform. Having a known value or expected range of signal phase allows return signals to be more readily manipulated during signal processing and detection. By using coherent signals, radar systems can detect Doppler shifts due to changes in relative velocity between the radar system and the target object.
Signal processing generally involves coherent integration to transform return signals from the time domain to the frequency domain. Typically, a fast Fourier transform (FFT) filter is used for the coherent integration. Signal processing can then be used to analyze the received return signals once they are represented in frequency domain form. However, even for frequency domain analysis, conventional radar systems require that the return signals have sufficient signal strength.
FIG. 1A is an FFT frequency domain representation of a received signal. The FFT shown in FIG. 1A indicates the relative velocity between the radar system and the target object. Target objects with higher velocities relative to the radar system have higher frequencies, and are shown shifted to the right. Target objects moving more slowly relative to the radar system have lower frequencies, and are shown shifted to the left.
By analyzing the FFTs corresponding to different time segments, changes in target velocity can be determined. Detecting target velocity changes within different time segments allows an approximation of acceleration to be made. However, to make such an approximate acceleration determination using a conventional radar signal processor, the received signal must be strong enough for detection in each FFT. If the SNR is too low for target detection of individual FFTs, lo velocity comparison can be made for determining acceleration.
In conventional radar systems, signal processing can be used to detect return signals and determine an unknown target acceleration for return signals characterized by high SNR. Conventional radar systems may also be able to detect the presence of return signals characterized by low SNR, but only if the acceleration component of the return signal is known.